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2018-07-06 Thread cloud-fan
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thanks, merging to master!


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retest this please.


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2018-07-06 Thread cloud-fan
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LGTM except 2 minor comments


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retest this please.


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[GitHub] spark issue #21611: [SPARK-24569][SQL] Aggregator with output type Option sh...

2018-07-05 Thread viirya
Github user viirya commented on the issue:

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Based on the comment, this null check is for preventing encoding a Product 
type to a null top-level row. For `Option[Int]`, it is encoded to an int column 
in a top-level row.

An example looks like:

```scala
val df = Seq(Some(1), Some(2), null, None).toDS()
df.show()
```

```
+-+
|value|
+-+
|1|
|2|
| null|
| null|
+-+
```


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[GitHub] spark issue #21611: [SPARK-24569][SQL] Aggregator with output type Option sh...

2018-07-04 Thread cloud-fan
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In `ExpressionEncoder.apply`, we have
```
val flat = !ScalaReflection.definedByConstructorParams(tpe)

val inputObject = BoundReference(0, ScalaReflection.dataTypeFor[T], 
nullable = !cls.isPrimitive)
val nullSafeInput = if (flat) {
  inputObject
} else {
  // For input object of Product type, we can't encode it to row if 
it's null, as Spark SQL
  // doesn't allow top-level row to be null, only its columns can be 
null.
  AssertNotNull(inputObject, Seq("top level Product input object"))
}
```

does it mean we will not have the null check for `Option[Int]`?


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2018-07-03 Thread viirya
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ping @cloud-fan for taking a look again.


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retest this please.


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retest this please.


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[GitHub] spark issue #21611: [SPARK-24569][SQL] Aggregator with output type Option sh...

2018-06-28 Thread viirya
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A test of `join` is added. The change of Option of product encoder is 
removed.


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[GitHub] spark issue #21611: [SPARK-24569][SQL] Aggregator with output type Option sh...

2018-06-28 Thread cloud-fan
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SGTM


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[GitHub] spark issue #21611: [SPARK-24569][SQL] Aggregator with output type Option sh...

2018-06-28 Thread viirya
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I agree with you. So I think this PR should be focused on the first 
problem. Is it ok for you?


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[GitHub] spark issue #21611: [SPARK-24569][SQL] Aggregator with output type Option sh...

2018-06-28 Thread cloud-fan
Github user cloud-fan commented on the issue:

https://github.com/apache/spark/pull/21611
  
There are 2 problems:
1. `Option` is mistakenly mapped to a struct type. It's not only for 
aggregate, but join too
```
scala> val a = Seq(Some(1)).toDS
a: org.apache.spark.sql.Dataset[Some[Int]] = [value: int]

scala> val b = Seq(Some(1.2)).toDS
b: org.apache.spark.sql.Dataset[Some[Double]] = [value: double]

scala> a.joinWith(b, lit(true))
res2: org.apache.spark.sql.Dataset[(Some[Int], Some[Double])] = [_1: 
struct, _2: struct]
```

2. `Aggregator` can't use option of product.

I think these 2 problems can be solved separately, what do you think?


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[GitHub] spark issue #21611: [SPARK-24569][SQL] Aggregator with output type Option sh...

2018-06-26 Thread viirya
Github user viirya commented on the issue:

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This affects the dataset with `Aggregator` of output type `Option`. 

For normal dataset schema, it does affect the following case:

```scala
val ds = Seq(Some(1), None, null).toDS()
ds.show
ds.printSchema
```

Before:
```
[info] If the schema is inferred from a Scala tuple/case class, or a Java 
bean, please try to use scala.Option[_] or other nullable types (
e.g. java.lang.Integer instead of int/scala.Int).
```

After:
```scala
+-+
|value|
+-+
|1|
| null|
| null|
+-+

root
 |-- value: integer (nullable = true)
```

This dataset's schema is a row with a nullable integer. I feel that it 
should be allowed to have null.



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[GitHub] spark issue #21611: [SPARK-24569][SQL] Aggregator with output type Option sh...

2018-06-25 Thread cloud-fan
Github user cloud-fan commented on the issue:

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does this affect normal dataset schema?


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[GitHub] spark issue #21611: [SPARK-24569][SQL] Aggregator with output type Option sh...

2018-06-25 Thread viirya
Github user viirya commented on the issue:

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ping @cloud-fan 


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[GitHub] spark issue #21611: [SPARK-24569][SQL] Aggregator with output type Option sh...

2018-06-22 Thread viirya
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cc @cloud-fan for review.


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2018-06-22 Thread viirya
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retest this please.


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